Performance Modeling and Analysis of Wireless Local Area Networks with Bursty Traffic

The explosive increase in the use of mobile digital devices has posed great challenges in the design and implementation of Wireless Local Area Networks (WLANs). Ever-increasing demands for high-speed and ubiquitous digital communication have made WLANs an essential feature of everyday life. With audio and video forming the highest percentage of traffic generated by multimedia applications, a huge demand is placed for high speed WLANs that provide high Quality-of-Service (QoS) and can satisfy end user’s needs at a relatively low cost. Providing video and audio contents to end users at a satisfactory level with various channel quality and current battery capacities requires thorough studies on the properties of such traffic. In this regard, Medium Access Control (MAC) protocol of the 802.11 standard plays a vital role in the management and coordination of shared channel access and data transmission. Therefore, this research focuses on developing new efficient analytical models that evaluate the performance of WLANs and the MAC protocol in the presence of bursty, correlated and heterogeneous multimedia traffic using Batch Markovian Arrival Process (BMAP). BMAP can model the correlation between different packet size distributions and traffic rates while accurately modelling aggregated traffic which often possesses negative statistical properties. The research starts with developing an accurate traffic generator using BMAP to capture the existing correlations in multimedia traffics. For validation, the developed traffic generator is used as an arrival process to a queueing model and is analyzed based on average queue length and mean waiting time. The performance of BMAP/M/1 queue is studied under various number of states and maximum batch sizes of BMAP. The results clearly indicate that any increase in the number of states of the underlying Markov Chain of BMAP or maximum batch size, lead to higher burstiness and correlation of the arrival process, prompting the speed of the queue towards saturation. The developed traffic generator is then used to model traffic sources in IEEE 802.11 WLANs, measuring important QoS metrics of throughput, end-to-end delay, frame loss probability and energy consumption. Performance comparisons are conducted on WLANs under the influence of multimedia traffics modelled as BMAP, Markov Modulated Poisson Process and Poisson Process. The results clearly indicate that bursty traffics generated by BMAP demote network performance faster than other traffic sources under moderate to high loads. The model is also used to study WLANs with unsaturated, heterogeneous and bursty traffic sources. The effects of traffic load and network size on the performance of WLANs are investigated to demonstrate the importance of burstiness and heterogeneity of traffic on accurate evaluation of MAC protocol in wireless multimedia networks. The results of the thesis highlight the importance of taking into account the true characteristics of multimedia traffics for accurate evaluation of the MAC protocol in the design and analysis of wireless multimedia networks and technologies

Analysis of generic discrete-time buffer models with irregular packet arrival patterns

De kwaliteit van de multimediadiensten die worden aangeboden over de huidige breedband-communicatienetwerken, wordt in hoge mate bepaald door de performantie van de buffers die zich in de diverse netwerkele-menten (zoals schakelknooppunten, routers, modems, toegangsmultiplexers, netwerkinter- faces, ...) bevinden. In dit proefschrift bestuderen we de performantie van een dergelijke buffer met behulp van een geschikt stochastisch discrete-tijd wachtlijnmodel, waarbij we het geval van meerdere uitgangskanalen en (niet noodzakelijk identieke) pakketbronnen beschouwen, en de pakkettransmissietijden in eerste instantie één slot bedragen. De grillige, of gecorreleerde, aard van een pakketstroom die door een bron wordt gegenereerd, wordt gekarakteriseerd aan de hand van een algemeen D-BMAP (discrete-batch Markovian arrival process), wat een generiek kader creëert voor het beschrijven van een superpositie van dergelijke informatiestromen. In een later stadium breiden we onze studie uit tot het geval van transmissietijden met een algemene verdeling, waarbij we ons beperken tot een buffer met één enkel uitgangskanaal. De analyse van deze wachtlijnmodellen gebeurt hoofdzakelijk aan de hand van een particuliere wiskundig-analytische aanpak waarbij uitvoerig gebruik gemaakt wordt van probabiliteitsgenererende functies, die er toe leidt dat de diverse performantiematen (min of meer expliciet) kunnen worden uitgedrukt als functie van de systeemparameters. Dit resul-teert op zijn beurt in efficiënte en accurate berekeningsalgoritmen voor deze grootheden, die op relatief eenvoudige wijze geïmplementeerd kunnen worden

Analysis of queueing models with batch service

This dissertation is the result of my research work at the SMACS research group (Department of Telecommunications and Information Processing, Ghent University) and it concerns the analysis of queueing models with batch service. A queueing model basically is a mathematical abstraction of a situation where customers arrive and queue up until they receive some kind of service. These phenomena are omnipresent in real life: people waiting at a counter of a post office or bank, people in the waiting room of a doctor, airplanes waiting to take off, people waiting until they get connected with the call center, data packets which are temporarily stored into a buffer until the transmisssion channel is available, et cetera. The analysis of queueing models constitutes the subject of the applied mathematical discipline called queueing theory and amounts to answering questions such as “How many customers are waiting on average?”, “How long do customers have to wait?”, “Is there a large variation on the waiting time?”, “What is the probability that data packets are lost due to a full buffer?”, “What is the probability that a customer suffers a lengthy delay?”, et cetera. In queueing theory, the number of customers and their waiting time are often denominated by respectively buffer content and customer delay. In addition, the probability that a quantity, such as the buffer content or customer delay, is very large or lengthy, is generally called a tail probability. The models we investigate throughout this dissertation have in common that customers can be served in batches, meaning that several customers can be served simultaneously. An elevator can be viewed as a classic example, as several people can be transported simultaneously to another floor. Also, in a variety of production or transport processes several goods can be processed together. Furthermore, in quality control, classification of items as good or bad can often be achieved more economically by examining the items in groups rather than individually. If the result of a group test is good, all items within it can then be classified as good, whereas one or more items are bad in the opposite case, where the items can then be retested by considering smaller groups. Group testing is especially of importance when the percentage of bad items is small. In addition, in telecommunications networks, packets with the same destination and quality of service (QoS) requirements are often aggregated into so-called bursts and these bursts are transmitted over the network. This is mainly done for efficiency reasons, since only one header per aggregated burst has to be constructed, instead of one header per single information unit, thus leading to an increased throughput. Technologies using packet aggregation include for instance Optical burst switched (OBS) networks and IEEE 802.11n wireless local area networks (WLANs). An inherent aspect of batch service is that newly arriving customers cannot join the ongoing service, even if there is free capacity (we denominate the maximum number of customers that can be served simultaneously by server capacity). For instance, an arriving person cannot enter an elevator that has just left, even if space is available. This person has to wait until the elevator has transported its occupants to their requested floors and has returned, which might take a long time in high buildings. In view of this, it is of importance to take a well-considered decision when the server becomes available and finds less customers than it can serve in theory. This decision is called the service policy. A whole spectrum of service policies exist. The server could, for instance, start serving the already present customers immediately. Although the present customers benefit from this approach, capacity is wasted: customers that arrive later cannot join the ongoing service. An alternative for this so-called immediate-batch service policy is the full-batch service policy. In this case, the available server postpones service until the number of present customers reaches or exceeds the server capacity, which, in turn, has a negative effect on the delay of the customers waiting to form a full batch (postponing delay). The threshold-based policy is a kind of compromise between immediate-batch service policy and full-batch service policy. When the number of present customers is below some service threshold, service is postponed, whereas service is initiated when the number of present customers reaches or exceeds this threshold. It is important to realize that even with this compromise, long postponing delays are possible. Therefore, in this dissertation, we combine a thresholdbased policy with a timer mechanism that avoids excessive postponing delays. The purpose of this dissertation is to calculate a large spectrum of performance measures, which enable to evaluate a broad set of situations with batch service and aid in selecting an efficient service policy. The studied performance measures are moments, such as the mean value and variance, and tail probabilities of the buffer content and the customer delay. This dissertation is structured as follows. In chapter 1, we motivate our work and we introduce crucial concepts such as probability generating functions (PGFs), whose useful properties are frequently relied upon throughout the analysis. Then we deduce moments and tail probabilities of the buffer content in chapter 2. The resulting formulas still contain unknown probabilities that have to be calculated numerically. As this might become unfeasible in some cases, we compute in chapter 3 approximations for the buffer content. Next, moments and tail probabilities of the customer delay are covered in respectively chapters 4 and 5. In order to analyze the moments, we conceive the customer delay as the sum of two non-overlapping parts, whereas for the tail probabilities, it turns out to be more convenient to interpret the delay as the maximum of two time periods. Further, in real life the customer arrival process often exhibits some kind of dependency. For instance, if a large amount of customers have recently arrived, it is likely that many customers arrive in the near future, as it might be an indication of a peak moment. Therefore, we investigate in chapter 6 the influence of dependency in the arrival process on the behaviour of batch-service phenomena and on the selection of an efficient service policy. Finally, the main contributions are summarized in chapter 7

Traffic modeling in mobile internet protocol : version 6.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.Mobile Internet Protocol Version 6 (lPv6) is the new version of the Internet Protocol (IP) born out of the great success of Internet Protocol version 4 (IPv4). The motivation behind the development of Mobile IPv6 standard stems from user's demand for mobile devices which can connect and move seamlessly across a growing number of connectivity options. It is both suitable for mobility between subnets across homogenous and inhomogeneous media. The protocol allows a mobile node to communicate with other hosts after changing its point of attachment from one subnet to another. The huge address space available meets the requirements for rapid development of internet as the number of mobile nodes increases tremendously with the rapid expansion of the internet. Mobility, security and quality of service (QoS) being integrated in Mobile TPv6 makes it the important foundation stone for building the mobile information society and the future internet. Convergence between current network technologies: the intern et and mobile telephony is taking place, but the internet's IP routing was designed to work with conventional static nodes. Mobile IPv6 is therefore considered to be one of the key technologies for realizing convergence which enables seamless communication between fixed and mobile access networks. For this reason, there is numerous works in location registrations and mobility management, traffic modeling, QoS, routing procedures etc. To meet the increased demand for mobile telecommunications, traffic modeling is an important step towards understanding and solving performance problems in the future wireless IP networks. Understanding the nature of this traffic, identifying its characteristics and developing appropriate traffic models coupled with appropriate mobility management architectures are of great importance to the traffic engineering and performance evaluation of these networks. It is imperative that the mobility management used keeps providing good performance to mobile users and maintain network load due to signaling and packet delivery as low as possible. To reduce this load, Intemet Engineering Task Force (IETF) proposed a regional mobility management. The load is reduced by allowing local migrations to be handled locally transparent from the Home Agent and the Correspondent Node as the mobile nodes roams freely around the network. This dissertation tackles two major aspects. Firstly, we propose the dynamic regional mobility management (DRMM) architecture with the aim to minimize network load while keeping an optimal number of access routers in the region. The mobility management is dynamic based on the movement and population of the mobile nodes around the network. Most traffic models in telecommunication networks have been based on the exponential Poisson processes. This model unfortunately has been proved to be unsuitable for modeling busty IP traffic. Several approaches to model IP traffic using Markovian processes have been developed using the Batch Markovian Alrival Process (BMAP) by characterizing arrivals as batches of sizes of different distributions. The BMAP is constructed by generalizing batch Poisson processes to allow for non-exponential times between arrivals of batches while maintaining an underlying Markovian structure. The second aspect of this dissertation covers the traffic characterization. We give the analysis of an access router as a single server queue with unlimited waiting space under a non pre-emptive priority queuing discipline. We model the arrival process as a superposition of BMAP processes. We characterize the superimposed arrival processes using the BMAP presentation. We derive the queue length and waiting time for this type of queuing system. Performance of this traffic model is evaluated by obtaining numerical results in terms of queue length and waiting time and its distribution for the high and low priority traffic. We finally present a call admission control scheme that supports QoS

Online QoS/Revenue Management for Third Generation Mobile Communication Networks

This thesis shows how online management of both quality of service (QoS) and provider revenue can be performed in third generation (3G) mobile networks by adaptive control of system parameters to changing traffic conditions. As a main result, this approach is based on a novel call admission control and bandwidth degradation scheme for real-time traffic. The admission controller considers real-time calls with two priority levels: calls of high priority have a guaranteed bit-rate, whereas calls of low priority can be temporarily degraded to a lower bit-rate in order to reduce forced termination of calls due to a handover failure. A second contribution constitutes the development of a Markov model for the admission controller that incorporates important features of 3G mobile networks, such as code division multiple access (CDMA) intra- and inter-cell interference and soft handover. Online evaluation of the Markov model enables a periodical adjustment of the threshold for maximal call degradation according to the currently measured traffic in the radio access network and a predefined goal for optimization. Using distinct optimization goals, this allows optimization of both QoS and provider revenue. Performance studies illustrate the effectiveness of the proposed approach and show that QoS and provider revenue can be increased significantly with a moderate degradation of low-priority calls. Compared with existing admission control policies, the overall utilization of cell capacity is significantly improved using the proposed degradation scheme, which can be considered as an 'on demand' reservation of cell capacity.To enable online QoS/revenue management of both real-time and non real-time services, accurate analytical traffic models for non real-time services are required. This thesis identifies the batch Markovian arrival process (BMAP) as the analytically tractable model of choice for the joint characterization of packet arrivals and packet lengths. As a key idea, the BMAP is customized such that different packet lengths are represented by batch sizes of arrivals. Thus, the BMAP enables the 'two-dimensional', i.e., joint, characterization of packet arrivals and packet lengths, and is able to capture correlations between the packet arrival process and the packet length process. A novel expectation maximization (EM) algorithm is developed, and it is shown how to utilize the randomization technique and a stable calculation of Poisson jump probabilities effectively for computing time-dependent conditional expectations of a continuous-time Markov chain required by the expectation step of the EM algorithm. This methodological work enables the EM algorithm to be both efficient and numerical robust and constitutes an important step towards effective, analytically/numerically tractable traffic models. Case studies of measured IP traffic with different degrees of traffic burstiness evidently demonstrate the advantages of the BMAP modeling approach over other widely used analytically tractable models and show that the joint characterization of packet arrivals and packet lengths is decisively for realistic traffic modeling at packet level

Unreliable Retrial Queues in a Random Environment

This dissertation investigates stability conditions and approximate steady-state performance measures for unreliable, single-server retrial queues operating in a randomly evolving environment. In such systems, arriving customers that find the server busy or failed join a retrial queue from which they attempt to regain access to the server at random intervals. Such models are useful for the performance evaluation of communications and computer networks which are characterized by time-varying arrival, service and failure rates. To model this time-varying behavior, we study systems whose parameters are modulated by a finite Markov process. Two distinct cases are analyzed. The first considers systems with Markov-modulated arrival, service, retrial, failure and repair rates assuming all interevent and service times are exponentially distributed. The joint process of the orbit size, environment state, and server status is shown to be a tri-layered, level-dependent quasi-birth-and-death (LDQBD) process, and we provide a necessary and sufficient condition for the positive recurrence of LDQBDs using classical techniques. Moreover, we apply efficient numerical algorithms, designed to exploit the matrix-geometric structure of the model, to compute the approximate steady-state orbit size distribution and mean congestion and delay measures. The second case assumes that customers bring generally distributed service requirements while all other processes are identical to the first case. We show that the joint process of orbit size, environment state and server status is a level-dependent, M/G/1-type stochastic process. By employing regenerative theory, and exploiting the M/G/1-type structure, we derive a necessary and sufficient condition for stability of the system. Finally, for the exponential model, we illustrate how the main results may be used to simultaneously select mean time customers spend in orbit, subject to bound and stability constraints

MAP/PH/1 systems with group service: performance analysis under different admission strategies

2015 - 2016Recent advances in wireless communication networks led to possibility of multi-rate transmission of information. The queueing theory represents a valid tool to study how the performances of such communication systems can be improved, and to give proper solutions. Modeling a multi-rate transmission system, in terms of queueing theory, means that a particular discipline has to be considered: a group of requests from users can be processed simultaneously in parallel and processing of the whole group is supposed finished if processing of all individual requests belonging to this group is over. In order to model this typology of telecommunication systems, some particular assumption can be made on arrivals, which occur by a Markovian arrival process, and on service time and length of admission period, which are regulated by phase type distributions. Thus, in this thesis MAP/PH/1 queueing systems have been considered, with and without retrial to take into account all possible behaviours of the customers. The main goal of the research activity presented in this work is to introduce novel admission strategies for the described systems, in order to give a major contribute to the current performance analysys, in particular as regard the choice of the optimal length of admission period and optimal size of the groups. Dynamics of such systems are described by multidimensional Markov chains. Ergodicity condition for these Markov chains have been derived, stationary probability distribution of the states have been computed, formulas for the main performance measures of the system have been attained. Essential advantages of the proposed customer’s service disciplines have been numerically illustrated. [edited by author]I recenti progressi ottenuti per le reti di comunicazione wireless, permettono la trasmissione multi-frequenza delle informazioni. La teoria delle code rappresenta un valido strumento per studiare come le performance di tali sistemi di comunicazione possano essere migliorate, e individuare opportune soluzioni. In termini di teoria delle code, modellare un sistema di trasmissione multi-frequenza significa considerare una determinata disciplina: un gruppo di richieste da parte di utenti possono essere processate simultaneamente in parallelo, e il processo dell’intero gruppo risulta completato se tutte le richieste appartenenti a tale gruppo sono espletate. Al fine di modellare tale tipologia di sistemi di telecomunicazione, si possono definire particolari assunzioni sugli arrivi, determinati da processi di arrivo Markoviani, e sul tempo di servizio e lunghezza del periodo di ammissione, regolati da distribuzioni di tipo a fasi. Pertanto, in tale lavoro di tesi sono stati considerati sistemi a coda di tipo MAP/PH/1, con e senza retrial per considerare tutti i possibili comportamenti degli utenti. Il principale obiettivo dell’attivita` di ricerca presentata in tale lavoro `e introdurre nuove strategie di ammissione per i sistemi descritti, al fine di fornire un maggior contributo alle attuali analisi sulle performance, in particolare relativamente alla scelta della lunghezza ottimale del periodo di ammissione e la dimensione ottimale dei gruppi. Le dinamiche di tali sistemi sono descritte da catene di Markov multidimensionali. `E stata ricavata la condizione di ergodicit`a per tali catene di Markov, `e stata calcolata la distribuzione delle probabilita` stazionarie degli stati, e sono state ottenute le formule per le misure dei principali parametri prestazionali del sistema. I principali vantaggi delle discipline di servizio proposte sono state illustrate numericamente. [a cura dell'autore]XXIX n.s

The effect of workload dependence in systems: Experimental evaluation, analytic models, and policy development

This dissertation presents an analysis of performance effects of burstiness (formalized by the autocorrelation function) in multi-tiered systems via a 3-pronged approach, i.e., experimental measurements, analytic models, and policy development. This analysis considers (a) systems with finite buffers (e.g., systems with admission control that effectively operate as closed systems) and (b) systems with infinite buffers (i.e., systems that operate as open systems).;For multi-tiered systems with a finite buffer size, experimental measurements show that if autocorrelation exists in any of the tiers in a multi-tiered system, then autocorrelation propagates to all tiers of the system. The presence of autocorrelated flows in all tiers significantly degrades performance. Workload characterization in a real experimental environment driven by the TPC-W benchmark confirms the existence of autocorrelated flows, which originate from the autocorrelated service process of one of the tiers. A simple model is devised that captures the observed behavior. The model is in excellent agreement with experimental measurements and captures the propagation of autocorrelation in the multi-tiered system as well as the resulting performance trends.;For systems with an infinite buffer size, this study focuses on analytic models by proposing and comparing two families of approximations for the departure process of a BMAP/MAP/1 queue that admits batch correlated flows, and whose service time process may be autocorrelated. One approximation is based on the ETAQA methodology for the solution of M/G/1-type processes and the other arises from lumpability rules. Formal proofs are provided: both approximations preserve the marginal distribution of the inter-departure times and their initial correlation structures.;This dissertation also demonstrates how the knowledge of autocorrelation can be used to effectively improve system performance, D_EQAL, a new load balancing policy for clusters with dependent arrivals is proposed. D_EQAL separates jobs to servers according to their sizes as traditional load balancing policies do, but this separation is biased by the effort to reduce performance loss due to autocorrelation in the streams of jobs that are directed to each server. as a result of this, not all servers are equally utilized (i.e., the load in the system becomes unbalanced) but performance benefits of this load unbalancing are significant